RESUMEN
PURPOSE: Hepatotoxicity has emerged as a major cause of statin treatment interruption. Although organic anion-transporting polypeptide 1B1 (SLCO1B1), multidrug resistance protein 1 (ABCB1), and breast cancer resistance protein (ABCG2) have been identified as transporters of statins, knowledge of their role in statin-associated hepatotoxicity remains limited. Therefore, we aimed to conduct a comprehensive analysis to elucidate the association between hepatotoxicity and SLCO1B1, ABCB1, and ABCG2 polymorphisms. METHODS: This study retrospectively analyzed prospectively collected samples. We selected 10 single nucleotide polymorphisms (SNPs) of SLCO1B1, 9 SNPs of ABCB1, and 12 SNPs of ABCG2. We developed two models for multivariable analyses (Model I: clinical factors only; Model II: both clinical and genetic factors), and the attributable risk (%) of variables in Model II was determined. RESULTS: Among 851 patients, 66 (7.8%) developed hepatotoxicity. In Model I, lipophilic statins, atrial fibrillation (Afib), and diabetes mellitus showed a significant association with hepatotoxicity. In Model II, lipophilic statins and Afib, SLCO1B1 rs11045818 A allele, SLCO1B1 rs4149035 T allele, and ABCG2 rs2622629 TT genotype were associated with higher hepatotoxicity risk. Among them, the SLCO1B1 rs11045818 A allele exhibited the highest attributable risk (93.2%). The area under the receiver operating characteristic curve in Model I was 0.62 (95% CI: 0.55-0.69), and it was increased to 0.71 in Model II (95% CI: 0.64-0.77). CONCLUSION: This study investigated the correlation between hepatotoxicity and polymorphisms of transporter genes in patients taking statins. The findings could help improve personalized treatments for patients receiving statin therapy.
RESUMEN
Introduction: The purpose of this study is to identify the relationship between coenzyme Q 10 (CoQ10)-related gene polymorphisms and statin-related myotoxicity (SRM). Methods: We retrospectively analyzed prospectively collected samples from February to May 2021. To investigate the association between CoQ10-related genetic factors and SRM, we selected 37 single nucleotide polymorphisms from five genes (COQ2, COQ3, COQ5, COQ6, and COQ7). The odds ratio (OR) and adjusted OR with 95% confidence intervals (CI) were calculated for univariate and multivariable logistic regression analyses, respectively. Results: A total of 688 stroke patients were included in the analysis, including 56 SRM cases. In the multivariable analysis, two models were constructed using demographic factors only in model I, and demographic and genetic factors in model II. Compared to other statins, atorvastatin decreased the SRM risk whereas ezetimibe use increased the SRM risk in model I and model II. Patients with COQ2 rs4693075 G allele, COQ3 rs11548336 TT genotype, and COQ5 rs10849757 A allele had a 2.9-fold (95% CI: 1.6-5.3), 1.9-fold (95% CI: 1.1-3.5), and 3.3-fold (95% CI: 1.5-8.3) higher risk of SRM, respectively. Conclusion: This study could be utilized to develop a personalized medicine strategy in patients treated with statins.
RESUMEN
Introduction: Bleeding is one of the most undesirable complications of direct oral anticoagulants (DOACs). While the ryanodine receptor (RYR2) has been related to cardiac diseases, research on bleeding complications is lacking. This study aimed to elucidate the association between RYR2 and bleeding risk to develop the risk scoring system in patients treated with DOACs. Methods: This study was a retrospective analysis of prospectively collected samples. We selected ten SNPs within the RYR2 gene, and two models were constructed (Model I: demographic factors only, Model II: demographic and genetic factors) in multivariable analysis. Independent risk factors for bleeding were used to develop a risk scoring system. Results: A total of 447 patients were included, and 49 experienced either major bleeding or clinically relevant non-major bleeding. In Model I, patients using rivaroxaban and experiencing anemia exhibited an increased bleeding risk after adjusting for covariates. Upon incorporating genetic factors into Model I, a significant association with bleeding was also observed in cases of overdosing on DOACs and in patients with a creatinine clearance (CrCl) < 30 mL/min, in addition to rivaroxaban and anemia (Model II). Among genetic factors, RYR2 rs12594 GG, rs17682073 AA, rs3766871 GG, and rs6678625 T alleles were associated with bleeding complications. The area under the receiver operating characteristic curve (AUROC) of Model I was 0.670, whereas that of Model II increased to 0.803, demonstrating better performance with the inclusion of genetic factors. Using the significant variables in Model II, a risk scoring system was constructed. The predicted bleeding risks for scores of 0, 1-2, 3-4, 5-6, 7-8, and 9-10 points were 0%, 1.2%, 4.6%, 15.7%, 41.7%, and 73.3%, respectively. Conclusion: This study revealed an association between RYR2 and bleeding complications among patients taking DOACs and established a risk scoring system to support individualized DOAC treatment for these patients.
